Annemarie Turnwald
Biographic Data
| ID | 9419043 |
|---|---|
| NAME | Annemarie Turnwald |
| GIVEN NAMES | Annemarie |
| FAMILY NAME | Turnwald |
| SIGNATURE | TURNWALD A |
| AFFILIATIONS | Technical University of Munich |
| ORCID | 0000-0001-9491-5778 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2019 |
| H-INDEX | 0 |
Human-Like Motion Planning Based on Game Theoretic Decision Making
Robot motion planners are increasingly being equipped with an intriguing property: human likeness. This property can enhance human–robot interactions and is essential for a convincing computer animation of humans. This paper presents a (multi-agent) motion planner for dynamic environments that generates human-like motion. The presented motion planner stands out against other motion planners by explicitly modeling human-like decision making and ta…
Understanding Human Avoidance Behavior: Interaction-Aware Decision Making Based on Game Theory
Being aware of mutual influences between individuals is a major requirement a robot to efficiently operate in human populated environments. This is especially true for the navigation among humans with its mutual avoidance maneuvers. While humans easily manage this task, robotic systems are still facing problems. Most of the recent approaches concentrate on predicting the motions of humans individually and deciding afterwards. Thereby, interactivi…
No prominent works on this page.
Understanding Human Avoidance Behavior: Interaction-Aware Decision Making Based on Game Theory
Being aware of mutual influences between individuals is a major requirement a robot to efficiently operate in human populated environments. This is especially true for the navigation among humans with its mutual avoidance maneuvers. While humans easily manage this task, robotic systems are still facing problems. Most of the recent approaches concentrate on predicting the motions of humans individually and deciding afterwards. Thereby, interactivi…
Human-Like Motion Planning Based on Game Theoretic Decision Making
Robot motion planners are increasingly being equipped with an intriguing property: human likeness. This property can enhance human–robot interactions and is essential for a convincing computer animation of humans. This paper presents a (multi-agent) motion planner for dynamic environments that generates human-like motion. The presented motion planner stands out against other motion planners by explicitly modeling human-like decision making and ta…
Artificial Intelligence (2 works) · Computer Science (2 works) · Evacuation and Crowd Dynamics (2 works) · Human–computer interaction (2 works) · Reinforcement Learning in Robotics (2 works) · Animation (1 works) · Computer animation (1 works) · Computer vision (1 works) · Engineering (1 works) · Game theory (1 works)